1,434 research outputs found
Redistribution, capital income taxation and tax evasion
Factor mobility and tax evasión are two phenomena that constraint the effectiveness
of redistributive policies now used by the member countries of the European Union.
In this paper, a normative analysis of this fact is undertaken using a simple model
with two countries and two social classes, where capital is perfectly mobile and
labour is immobile. Each country complements the income of its workers, assumed to
be poor, with transfers. The latter are financed with two taxes on capital income. The
first one, following the origin principie, alters the retum and intemational allocation
of capital. The second one, following the residence principie, induces the evasión of
capitalists' incomes. Each government chooses the optimal mix of capital taxes that
maximizes the welfare of its citizens with no regard on the repercussions on its
neighbour country. A numerical exercise is built to examine the sensitivity of the
resulting non cooperative equilibrium to the aversión to inequality exhibited by the
different governments as well as to the factor endowments of their respective
countries
An Empirical Study on the Joint Impact of Feature Selection and Data Re-sampling on Imbalance Classification
In predictive tasks, real-world datasets often present di erent degrees of imbalanced (i.e., long-tailed or skewed) distributions.
While the majority (the head or the most frequent) classes have su cient samples, the minority (the tail or
the less frequent or rare) classes can be under-represented by a rather limited number of samples. Data pre-processing
has been shown to be very e ective in dealing with such problems. On one hand, data re-sampling is a common
approach to tackling class imbalance. On the other hand, dimension reduction, which reduces the feature space, is a
conventional technique for reducing noise and inconsistencies in a dataset. However, the possible synergy between
feature selection and data re-sampling for high-performance imbalance classification has rarely been investigated before.
To address this issue, we carry out a comprehensive empirical study on the joint influence of feature selection and
re-sampling on two-class imbalance classification. Specifically, we study the performance of two opposite pipelines
for imbalance classification by applying feature selection before or after data re-sampling. We conduct a large number
of experiments, with a total of 9225 tests, on 52 publicly available datasets, using 9 feature selection methods, 6 resampling
approaches for class imbalance learning, and 3 well-known classification algorithms. Experimental results
show that there is no constant winner between the two pipelines; thus both of them should be considered to derive
the best performing model for imbalance classification. We find that the performance of an imbalance classification
model not only depends on the classifier adopted and the ratio between the number of majority and minority samples,
but also depends on the ratio between the number of samples and features. Overall, this study should provide new
reference value for researchers and practitioners in imbalance learning.TIN2017-89517-
Speech emotion recognition via multiple fusion under spatial–temporal parallel network
The authors are grateful to the anonymous reviewers and the editor for their valuable comments and suggestions. This work was supported by the National Natural Science Foundation of China (No. 61702066), the Chongqing Research Program of Basic Research and Frontier Technology, China (No. cstc2021jcyj-msxmX0761) and partially supported by Project PID2020-119478GB-I00 funded by MICINN/AEI/10.13039/501100011033 and by Project A-TIC-434- UGR20 funded by FEDER/Junta de Andalucía Consejería de Transformación Económica, Industria, Conocimiento Universidades.Speech, as a necessary way to express emotions, plays a vital role in human communication. With the continuous deepening of research on emotion recognition in human-computer interaction, speech emotion recognition (SER) has become an essential task to improve the human-computer interaction experience. When performing emotion feature extraction of speech, the method of cutting the speech spectrum will destroy the continuity of speech. Besides, the method of using the cascaded structure without cutting the speech spectrum cannot simultaneously extract speech spectrum information from both temporal and spatial domains. To this end, we propose a spatial-temporal parallel network for speech emotion recognition without cutting the speech spectrum. To further mix the temporal and spatial features, we design a novel fusion method (called multiple fusion) that combines the concatenate fusion and ensemble strategy. Finally, the experimental results on five datasets demonstrate that the proposed method outperforms state-of-the-art methods.National Natural Science Foundation of China 61702066Chongqing Research Program of Basic Research and Frontier Technology, China cstc2021jcyj-msxmX0761MICINN/AEI/10.13039/501100011033: PID2020-119478GB-I00FEDER/Junta de Andalucía A-TIC-434- UGR2
Capacidad Cardiovascular en Adultos Sedentarios Obesos sometidos a prueba de esfuerzo en banda sin fin con Protocolo de Bruce modificado en el Centro de Medicina de la Actividad Física y el Deporte, año 2012
El estilo de vida sedentario es uno de los principales factores de riesgo para enfermedades de alta prevalencia, como la diabetes tipo 2, las enfermedades cardiovasculares, la osteoporosis y algunos cánceres. (1). La asociación del sedentarismo con la actual pandemia de obesidad y con el síndrome metabólico (SM) es clara. En consecuencia, el sedentarismo es un factor asociado con una peor calidad de vida y un incremento de la mortalidad general
An extension on "statistical comparisons of classifiers over multiple data sets" for all pairwise comparisons
In a recently published paper in JMLR, Demsar
(2006) recommends a set of non-parametric statistical tests and procedures which can be safely used for comparing the performance
of classifiers over multiple data sets. After studying the paper, we realize that the
paper correctly introduces the basic procedures and some of the most advanced
ones when comparing a control method.
However, it does not deal with some advanced
topics in depth. Regarding these topics,
we focus on more powerful proposals of statistical procedures for comparing n*n classifiers.
Moreover, we illustrate an easy way of obtaining adjusted and comparable p-values
in multiple comparison procedures.This research has been supported by the project TIN2005-08386-C05-01. S. García holds a FPU scholarship from Spanish Ministry of Education and Science
EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population
Background: Epilepsy is one of the most common neurological conditions globally, and the fourth most common
in the United States. Recurrent non-provoked seizures characterize it and have huge impacts on the quality of life
and financial impacts for affected individuals. A rapid and accurate diagnosis is essential in order to instigate and
monitor optimal treatments. There is also a compelling need for the accurate interpretation of epilepsy due to the
current scarcity in neurologist diagnosticians and a global inequity in access and outcomes. Furthermore, the
existing clinical and traditional machine learning diagnostic methods exhibit limitations, warranting the need to
create an automated system using deep learning model for epilepsy detection and monitoring using a huge
database.
Method: The EEG signals from 35 channels were used to train the deep learning-based transformer model named
(EpilepsyNet). For each training iteration, 1-min-long data were randomly sampled from each participant.
Thereafter, each 5-s epoch was mapped to a matrix using the Pearson Correlation Coefficient (PCC), such that the
bottom part of the triangle was discarded and only the upper triangle of the matrix was vectorized as input data.
PCC is a reliable method used to measure the statistical relationship between two variables. Based on the 5 s of
data, single embedding was performed thereafter to generate a 1-dimensional array of signals. In the final stage,
a positional encoding with learnable parameters was added to each correlation coefficient’s embedding before
being fed to the developed EpilepsyNet as input data to epilepsy EEG signals. The ten-fold cross-validation
technique was used to generate the model.
Results: Our transformer-based model (EpilepsyNet) yielded high classification accuracy, sensitivity, specificity
and positive predictive values of 85%, 82%, 87%, and 82%, respectively.
Conclusion: The proposed method is both accurate and robust since ten-fold cross-validation was employed to
evaluate the performance of the model. Compared to the deep models used in existing studies for epilepsy
diagnosis, our proposed method is simple and less computationally intensive. This is the earliest study to have
uniquely employed the positional encoding with learnable parameters to each correlation coefficient’s embedding
together with the deep transformer model, using a huge database of 121 participants for epilepsy detection.
With the training and validation of the model using a larger dataset, the same study approach can be extended for
the detection of other neurological conditions, with a transformative impact on neurological diagnostics
worldwide
Value Co-Creation in Ecotourism: Finding Solutions in a Digital Era
This study aims to identify the main actors in the ecotourism online value co-creation ecosystem. With the ever-increasing demand to which the ecotourism sector has been subject in recent years, there is a need for business models featuring interactive tools that allow ecotourists to participate and co-create their own experiences. Not only will ecotourism businesses and ecotourists participate in this process, but so too will several other stakeholders, becoming key actors in the co-creation of value.
Ecotourism, being of a hedonic and experiential nature, requires strategies that are geared towards enjoyment of the joint value co-creation experience. With this finality, we present some factors, such as motivation, that are necessary for the ecotourist's value co-creation, as well as various other aspects that influence their behavior.
Our expectation is that value co-creation will have a positive effect on the behavior and experiences of tourists when it comes to developing ecotourism products and services. Specifically, we expect that the implementation of a co-creation strategy will lead to greater satisfaction and loyalty. Accordingly, drawing on the existing literature, we present a theoretical proposal of the antecedents and consequents that affect and enable online value co-creation by ecotourists
Detección y aislamiento robusto de fallas en tiempo finito
Seguridad y confiabilidad en la industria es una prioridad de la actualidad. Una forma de apoyarla es mediante el uso de sistemas de supervisión del desempeño, los cuales incluyen diagnóstico de fallas así como mecanismos de tolerancia de fallas. En este trabajo se propone un algoritmo robusto que converge en tiempo finito para la detección y aislamiento de fallas, permitiendo aumentar la confiabilidad de la detección a partir del tiempo de convergencia, el cual puede ser fijado arbitrariamente. El resultado se logra sin alterar la dinámica propia del residuo. El algoritmo es probado con un modelo de simulación
教师视角下对小学教育资源包容性使用的研究
Addressing the diversity of students from an inclusive perspective requires that schools carry out self-study processes that help them analyse the strengths and weaknesses that hinder the full integration of students. The main objective of this research was to analyse the strengths and obstacles in the use and availability of materials and education resources present in a private school of primary education.
A descriptive and quantitative case study was carried out, in which the opinion of 23 professionals was analyzed through the instrument “Guía de Autoevaluación de Centro para la Atención a la Diversidad (ACADI)”, specifically, the “Resources” section.
The results showed that the main strengths are the final purpose the centre gives to the resources, the accessibility of its facilities, the engagement of families and the coordination between professionals to respond to the diversity of the centre. The lack of resources for teachers to put their training into practice, the lack of technical support for students who need it to access information, the lack of activities for teacher training, and the lack of consideration given to students’ interests when developing the curriculum were identified as the main barriers to inclusive education.
We conclude by stating that identifying the facilitating and hindering elements present in this centre for inclusive education helps us to start progressing on the road to quality education with all and for all.Atender la diversidad del alumnado desde el paradigma de la inclusión requiere que los centros educativos realicen procesos de autorreflexión que les ayuden a analizar cuáles son las fortalezas y debilidades que dificultan la plena participación de todo el alumnado. El objetivo de esta investigación fue analizar las fortalezas y barreras en el uso y disposición de los recursos presentes en un colegio concertado en la etapa de educación primaria.
Se realizó un estudio de caso de corte descriptivo y cuantitativo, en el que se analizó la opinión de 23 profesionales encuestados a través del instrumento “Guía de Autoevaluación de Centro para la Atención a la Diversidad (ACADI)”, en concreto, la dimensión referida a “Recursos”.
Los resultados mostraron como principales fortalezas la finalidad que el centro da a los recursos existentes en el mismo, la accesibilidad a sus instalaciones, la participación de las familias y la coordinación entre el profesorado para responder a la diversidad del centro. Como barreras para favorecer la inclusión se detectaron la falta de recursos para que el profesorado pueda poner en práctica su formación, la escasez de ayudas técnicas para el alumnado que las requiera, la carencia de actividades de formación para el profesorado, así como la escasa consideración de partir de los intereses del alumnado para construir el currículo.
Las conclusiones muestran que conocer los recursos facilitadores y obstaculizadores presentes en este centro, para la inclusión educativa de su alumnado, posibilitará el emprendimiento de líneas de mejora en el camino hacia una educación de calidad con todos y para todos.从包容范式面对学生的多样性需要学校进行一个自我反思的过程,以帮助他们分析阻碍所有学生充分参与的优势和劣势。本研究的目的是分析初等教育阶段半公半私学校资源使用和配置的优势和障碍。
我们进行描述性和定量的案例研究,通过“关注多样性中心(ACADI)自我评估指南”工具对23名受访专业人士的意见进行分析,其中具体的维度为“资源”维度。
结果表明,该中心的主要优势在于其现有资源的目的、设施的可及性、家庭的参与以及教师之间的协调,以应对学校的多样性需求。其阻碍包容性的障碍包括教师缺乏将培训付诸实践的资源、缺乏为有需要的学生提供的技术援助、缺乏对教师的培训活动以及从学生利益出发的考虑有限。学生构建课程。
结论表明,了解该包容性教育中心存在的促进和阻碍因素,有助于我们开始在全民优质教育的道路上取得进展
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